Artificial Intelligence has moved quickly from experiment to expectation.
Across workplaces, staff are already using AI tools to write emails, summarise meetings, generate reports and answer questions. But inside learning and development teams, a bigger question is emerging:
What happens when AI is used not just to consume information, but to create and share knowledge across an organisation?
That was the focus of a recent webinar hosted by Totara where speakers explored how AI functionality inside the platform could help organisations move beyond traditional top-down learning models.
The message was clear: the future of workplace learning may depend less on creating more courses, and more on unlocking the expertise that already exists inside businesses.
The bottleneck facing learning teams
For years, most workplace learning has followed the same pattern.
A central L&D team creates courses. Staff complete them. Updates are requested. Compliance changes arrive. New training needs appear. The cycle repeats.
The problem is scale.
Many learning teams are small, stretched and constantly reacting to new demands. Valuable expertise often sits elsewhere across the organisation – with engineers, managers, sales teams, healthcare professionals or frontline staff – but turning that knowledge into structured learning has traditionally taken time.
As one speaker explained during the session:
“We don’t really have a knowledge problem. We have a capture and sharing problem.”
That challenge has become even more visible as organisations move faster and information changes more frequently.
Instead of waiting for formal training, employees often turn to colleagues directly through messaging platforms, informal chats or shared documents. While effective in the short term, this creates new pressures on experienced staff and makes knowledge difficult to scale consistently.
AI as a “co-pilot”, not a replacement
One of the strongest themes throughout the webinar was that AI is not being positioned as a replacement for learning teams.
Instead, the technology is being presented as a support tool – helping subject matter experts contribute knowledge more quickly and confidently.
Inside the Totara Learn LMS, AI tools can assist users in generating draft content, summarising long passages, creating knowledge checks and even producing supporting imagery.
The idea is simple.
Someone with expertise may not have the time, confidence or writing ability to build polished learning materials from scratch. AI can reduce that friction by turning a blank page into a starting point within seconds.
Rather than expecting L&D teams to create everything themselves, organisations can begin enabling contribution at scale.
Turning learners into creators
The webinar repeatedly returned to a broader shift in mindset.
Traditionally, learners consume content.
But AI opens the possibility for learners to become contributors as well.
That could mean:
- Sharing practical insights
- Creating quick resources
- Building draft learning materials
- Improving existing content
- Generating summaries or quizzes
In practice, this changes the role of the learning team.
Instead of acting solely as content creators, L&D professionals increasingly become facilitators, reviewers and quality managers – helping shape and govern learning created across the organisation.
The speakers argued that this approach could lead to faster knowledge sharing and more relevant learning experiences because the information comes directly from people applying it in real-world situations.
Faster content creation
One demonstration during the webinar showed how AI tools inside Totara can generate draft learning content from short prompts.
Users can ask the platform to create introductory material, expand ideas, summarise text or rewrite sections in different styles.
The aim is not necessarily to publish AI-generated text untouched.
Instead, the generated content acts as a first draft – something experts can refine, improve and personalise.
For many organisations, that could significantly reduce the time required to create or update learning resources.
This becomes particularly important in areas such as:
- Compliance training
- Policy updates
- Product knowledge
- Operational procedures
- Healthcare guidance
- Technical documentation
Where information changes regularly, speed matters.
Knowledge checks and engagement
Another feature highlighted was AI-assisted “knowledge checks”.
Users can upload documents or text-based resources, and the platform can automatically generate quizzes or understanding checks based on the material.
The purpose is less about formal assessment and more about reinforcing learning and encouraging engagement.
It also provides organisations with a lightweight way of confirming whether employees have interacted with key information – something increasingly important in regulated industries.
A wider change in workplace learning
Perhaps the most significant takeaway from the session was not the technology itself, but what it represents.
For years, organisations have struggled to scale internal knowledge effectively.
AI may finally offer a practical way to lower the barrier between expertise and learning.
If implemented carefully, that could help businesses:
- Share knowledge faster
- Reduce pressure on L&D teams
- Capture expertise before it is lost
- Encourage collaborative learning
- Keep training more up to date
- Increase learner engagement
There are still questions around governance, quality control, privacy and accuracy. Even the webinar speakers stressed the importance of human oversight.
But the direction of travel is becoming increasingly clear.
The organisations that succeed with AI learning tools may not simply be the ones creating more content.
They may be the ones that make it easiest for people to share what they already know.
Want to leverage AI for workplace learning? Contact us at Webanywhere for an informal discussion about your needs and goals.